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Hessian-regularized co-training for social activity recognition.
PUBLISHED: 01-01-2014
Co-training is a major multi-view learning paradigm that alternately trains two classifiers on two distinct views and maximizes the mutual agreement on the two-view unlabeled data. Traditional co-training algorithms usually train a learner on each view separately and then force the learners to be consistent across views. Although many co-trainings have been developed, it is quite possible that a learner will receive erroneous labels for unlabeled data when the other learner has only mediocre accuracy. This usually happens in the first rounds of co-training, when there are only a few labeled examples. As a result, co-training algorithms often have unstable performance. In this paper, Hessian-regularized co-training is proposed to overcome these limitations. Specifically, each Hessian is obtained from a particular view of examples; Hessian regularization is then integrated into the learner training process of each view by penalizing the regression function along the potential manifold. Hessian can properly exploit the local structure of the underlying data manifold. Hessian regularization significantly boosts the generalizability of a classifier, especially when there are a small number of labeled examples and a large number of unlabeled examples. To evaluate the proposed method, extensive experiments were conducted on the unstructured social activity attribute (USAA) dataset for social activity recognition. Our results demonstrate that the proposed method outperforms baseline methods, including the traditional co-training and LapCo algorithms.
To enable intuitive operation of powered artificial legs, an interface between user and prosthesis that can recognize the user's movement intent is desired. A novel neural-machine interface (NMI) based on neuromuscular-mechanical fusion developed in our previous study has demonstrated a great potential to accurately identify the intended movement of transfemoral amputees. However, this interface has not yet been integrated with a powered prosthetic leg for true neural control. This study aimed to report (1) a flexible platform to implement and optimize neural control of powered lower limb prosthesis and (2) an experimental setup and protocol to evaluate neural prosthesis control on patients with lower limb amputations. First a platform based on a PC and a visual programming environment were developed to implement the prosthesis control algorithms, including NMI training algorithm, NMI online testing algorithm, and intrinsic control algorithm. To demonstrate the function of this platform, in this study the NMI based on neuromuscular-mechanical fusion was hierarchically integrated with intrinsic control of a prototypical transfemoral prosthesis. One patient with a unilateral transfemoral amputation was recruited to evaluate our implemented neural controller when performing activities, such as standing, level-ground walking, ramp ascent, and ramp descent continuously in the laboratory. A novel experimental setup and protocol were developed in order to test the new prosthesis control safely and efficiently. The presented proof-of-concept platform and experimental setup and protocol could aid the future development and application of neurally-controlled powered artificial legs.
24 Related JoVE Articles!
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Morris Water Maze Experiment
Authors: Joseph Nunez.
Institutions: Michigan State University (MSU).
The Morris water maze is widely used to study spatial memory and learning. Animals are placed in a pool of water that is colored opaque with powdered non-fat milk or non-toxic tempera paint, where they must swim to a hidden escape platform. Because they are in opaque water, the animals cannot see the platform, and cannot rely on scent to find the escape route. Instead, they must rely on external/extra-maze cues. As the animals become more familiar with the task, they are able to find the platform more quickly. Developed by Richard G. Morris in 1984, this paradigm has become one of the "gold standards" of behavioral neuroscience.
Behavior, Issue 19, Declarative, Hippocampus, Memory, Procedural, Rodent, Spatial Learning
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Training Synesthetic Letter-color Associations by Reading in Color
Authors: Olympia Colizoli, Jaap M. J. Murre, Romke Rouw.
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
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Corticospinal Excitability Modulation During Action Observation
Authors: Luisa Sartori, Sonia Betti, Umberto Castiello.
Institutions: Universita degli Studi di Padova.
This study used the transcranial magnetic stimulation/motor evoked potential (TMS/MEP) technique to pinpoint when the automatic tendency to mirror someone else's action becomes anticipatory simulation of a complementary act. TMS was delivered to the left primary motor cortex corresponding to the hand to induce the highest level of MEP activity from the abductor digiti minimi (ADM; the muscle serving little finger abduction) as well as the first dorsal interosseus (FDI; the muscle serving index finger flexion/extension) muscles. A neuronavigation system was used to maintain the position of the TMS coil, and electromyographic (EMG) activity was recorded from the right ADM and FDI muscles. Producing original data with regard to motor resonance, the combined TMS/MEP technique has taken research on the perception-action coupling mechanism a step further. Specifically, it has answered the questions of how and when observing another person's actions produces motor facilitation in an onlooker's corresponding muscles and in what way corticospinal excitability is modulated in social contexts.
Behavior, Issue 82, action observation, transcranial magnetic stimulation, motor evoked potentials, corticospinal excitability
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
Authors: Marc N. Coutanche, Sharon L. Thompson-Schill.
Institutions: University of Pennsylvania.
It is now appreciated that condition-relevant information can be present within distributed patterns of functional magnetic resonance imaging (fMRI) brain activity, even for conditions with similar levels of univariate activation. Multi-voxel pattern (MVP) analysis has been used to decode this information with great success. FMRI investigators also often seek to understand how brain regions interact in interconnected networks, and use functional connectivity (FC) to identify regions that have correlated responses over time. Just as univariate analyses can be insensitive to information in MVPs, FC may not fully characterize the brain networks that process conditions with characteristic MVP signatures. The method described here, informational connectivity (IC), can identify regions with correlated changes in MVP-discriminability across time, revealing connectivity that is not accessible to FC. The method can be exploratory, using searchlights to identify seed-connected areas, or planned, between pre-selected regions-of-interest. The results can elucidate networks of regions that process MVP-related conditions, can breakdown MVPA searchlight maps into separate networks, or can be compared across tasks and patient groups.
Neuroscience, Issue 89, fMRI, MVPA, connectivity, informational connectivity, functional connectivity, networks, multi-voxel pattern analysis, decoding, classification, method, multivariate
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
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Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
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Getting to Compliance in Forced Exercise in Rodents: A Critical Standard to Evaluate Exercise Impact in Aging-related Disorders and Disease
Authors: Jennifer C. Arnold, Michael F. Salvatore.
Institutions: Louisiana State University Health Sciences Center.
There is a major increase in the awareness of the positive impact of exercise on improving several disease states with neurobiological basis; these include improving cognitive function and physical performance. As a result, there is an increase in the number of animal studies employing exercise. It is argued that one intrinsic value of forced exercise is that the investigator has control over the factors that can influence the impact of exercise on behavioral outcomes, notably exercise frequency, duration, and intensity of the exercise regimen. However, compliance in forced exercise regimens may be an issue, particularly if potential confounds of employing foot-shock are to be avoided. It is also important to consider that since most cognitive and locomotor impairments strike in the aged individual, determining impact of exercise on these impairments should consider using aged rodents with a highest possible level of compliance to ensure minimal need for test subjects. Here, the pertinent steps and considerations necessary to achieve nearly 100% compliance to treadmill exercise in an aged rodent model will be presented and discussed. Notwithstanding the particular exercise regimen being employed by the investigator, our protocol should be of use to investigators that are particularly interested in the potential impact of forced exercise on aging-related impairments, including aging-related Parkinsonism and Parkinson’s disease.
Behavior, Issue 90, Exercise, locomotor, Parkinson’s disease, aging, treadmill, bradykinesia, Parkinsonism
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Flat-floored Air-lifted Platform: A New Method for Combining Behavior with Microscopy or Electrophysiology on Awake Freely Moving Rodents
Authors: Mikhail Kislin, Ekaterina Mugantseva, Dmitry Molotkov, Natalia Kulesskaya, Stanislav Khirug, Ilya Kirilkin, Evgeny Pryazhnikov, Julia Kolikova, Dmytro Toptunov, Mikhail Yuryev, Rashid Giniatullin, Vootele Voikar, Claudio Rivera, Heikki Rauvala, Leonard Khiroug.
Institutions: University of Helsinki, Neurotar LTD, University of Eastern Finland, University of Helsinki.
It is widely acknowledged that the use of general anesthetics can undermine the relevance of electrophysiological or microscopical data obtained from a living animal’s brain. Moreover, the lengthy recovery from anesthesia limits the frequency of repeated recording/imaging episodes in longitudinal studies. Hence, new methods that would allow stable recordings from non-anesthetized behaving mice are expected to advance the fields of cellular and cognitive neurosciences. Existing solutions range from mere physical restraint to more sophisticated approaches, such as linear and spherical treadmills used in combination with computer-generated virtual reality. Here, a novel method is described where a head-fixed mouse can move around an air-lifted mobile homecage and explore its environment under stress-free conditions. This method allows researchers to perform behavioral tests (e.g., learning, habituation or novel object recognition) simultaneously with two-photon microscopic imaging and/or patch-clamp recordings, all combined in a single experiment. This video-article describes the use of the awake animal head fixation device (mobile homecage), demonstrates the procedures of animal habituation, and exemplifies a number of possible applications of the method.
Empty Value, Issue 88, awake, in vivo two-photon microscopy, blood vessels, dendrites, dendritic spines, Ca2+ imaging, intrinsic optical imaging, patch-clamp
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Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials
Authors: Jason R. Themanson.
Institutions: Illinois Wesleyan University.
Social exclusion is a complex social phenomenon with powerful negative consequences. Given the impact of social exclusion on mental and emotional health, an understanding of how perceptions of social exclusion develop over the course of a social interaction is important for advancing treatments aimed at lessening the harmful costs of being excluded. To date, most scientific examinations of social exclusion have looked at exclusion after a social interaction has been completed. While this has been very helpful in developing an understanding of what happens to a person following exclusion, it has not helped to clarify the moment-to-moment dynamics of the process of social exclusion. Accordingly, the current protocol was developed to obtain an improved understanding of social exclusion by examining the patterns of event-related brain activation that are present during social interactions. This protocol allows greater precision and sensitivity in detailing the social processes that lead people to feel as though they have been excluded from a social interaction. Importantly, the current protocol can be adapted to include research projects that vary the nature of exclusionary social interactions by altering how frequently participants are included, how long the periods of exclusion will last in each interaction, and when exclusion will take place during the social interactions. Further, the current protocol can be used to examine variables and constructs beyond those related to social exclusion. This capability to address a variety of applications across psychology by obtaining both neural and behavioral data during ongoing social interactions suggests the present protocol could be at the core of a developing area of scientific inquiry related to social interactions.
Behavior, Issue 93, Event-related brain potentials (ERPs), Social Exclusion, Neuroscience, N2, P3, Cognitive Control
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Community-based Adapted Tango Dancing for Individuals with Parkinson's Disease and Older Adults
Authors: Madeleine E. Hackney, Kathleen McKee.
Institutions: Emory University School of Medicine, Brigham and Woman‘s Hospital and Massachusetts General Hospital.
Adapted tango dancing improves mobility and balance in older adults and additional populations with balance impairments. It is composed of very simple step elements. Adapted tango involves movement initiation and cessation, multi-directional perturbations, varied speeds and rhythms. Focus on foot placement, whole body coordination, and attention to partner, path of movement, and aesthetics likely underlie adapted tango’s demonstrated efficacy for improving mobility and balance. In this paper, we describe the methodology to disseminate the adapted tango teaching methods to dance instructor trainees and to implement the adapted tango by the trainees in the community for older adults and individuals with Parkinson’s Disease (PD). Efficacy in improving mobility (measured with the Timed Up and Go, Tandem stance, Berg Balance Scale, Gait Speed and 30 sec chair stand), safety and fidelity of the program is maximized through targeted instructor and volunteer training and a structured detailed syllabus outlining class practices and progression.
Behavior, Issue 94, Dance, tango, balance, pedagogy, dissemination, exercise, older adults, Parkinson's Disease, mobility impairments, falls
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Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Authors: Joel Ramirez, Christopher J.M. Scott, Alicia A. McNeely, Courtney Berezuk, Fuqiang Gao, Gregory M. Szilagyi, Sandra E. Black.
Institutions: Sunnybrook Health Sciences Centre, University of Toronto.
Obtaining in vivo human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are exacerbated when significant brain atrophy and age-related white matter changes (e.g. Leukoaraiosis) are present. Lesion Explorer (LE) is an accurate and reliable neuroimaging pipeline specifically developed to address such issues commonly observed on MRI of Alzheimer's disease and normal elderly. The pipeline is a complex set of semi-automatic procedures which has been previously validated in a series of internal and external reliability tests1,2. However, LE's accuracy and reliability is highly dependent on properly trained manual operators to execute commands, identify distinct anatomical landmarks, and manually edit/verify various computer-generated segmentation outputs. LE can be divided into 3 main components, each requiring a set of commands and manual operations: 1) Brain-Sizer, 2) SABRE, and 3) Lesion-Seg. Brain-Sizer's manual operations involve editing of the automatic skull-stripped total intracranial vault (TIV) extraction mask, designation of ventricular cerebrospinal fluid (vCSF), and removal of subtentorial structures. The SABRE component requires checking of image alignment along the anterior and posterior commissure (ACPC) plane, and identification of several anatomical landmarks required for regional parcellation. Finally, the Lesion-Seg component involves manual checking of the automatic lesion segmentation of subcortical hyperintensities (SH) for false positive errors. While on-site training of the LE pipeline is preferable, readily available visual teaching tools with interactive training images are a viable alternative. Developed to ensure a high degree of accuracy and reliability, the following is a step-by-step, video-guided, standardized protocol for LE's manual procedures.
Medicine, Issue 86, Brain, Vascular Diseases, Magnetic Resonance Imaging (MRI), Neuroimaging, Alzheimer Disease, Aging, Neuroanatomy, brain extraction, ventricles, white matter hyperintensities, cerebrovascular disease, Alzheimer disease
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Using an Automated 3D-tracking System to Record Individual and Shoals of Adult Zebrafish
Authors: Hans Maaswinkel, Liqun Zhu, Wei Weng.
Institutions: xyZfish.
Like many aquatic animals, zebrafish (Danio rerio) moves in a 3D space. It is thus preferable to use a 3D recording system to study its behavior. The presented automatic video tracking system accomplishes this by using a mirror system and a calibration procedure that corrects for the considerable error introduced by the transition of light from water to air. With this system it is possible to record both single and groups of adult zebrafish. Before use, the system has to be calibrated. The system consists of three modules: Recording, Path Reconstruction, and Data Processing. The step-by-step protocols for calibration and using the three modules are presented. Depending on the experimental setup, the system can be used for testing neophobia, white aversion, social cohesion, motor impairments, novel object exploration etc. It is especially promising as a first-step tool to study the effects of drugs or mutations on basic behavioral patterns. The system provides information about vertical and horizontal distribution of the zebrafish, about the xyz-components of kinematic parameters (such as locomotion, velocity, acceleration, and turning angle) and it provides the data necessary to calculate parameters for social cohesions when testing shoals.
Behavior, Issue 82, neuroscience, Zebrafish, Danio rerio, anxiety, Shoaling, Pharmacology, 3D-tracking, MK801
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Institutions: Princeton University.
The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (, a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
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Determining heat and mechanical pain threshold in inflamed skin of human subjects
Authors: Martin S Angst, Martha Tingle, Nicholas G Phillips, Brendan Carvalho.
Institutions: Stanford University School of Medicine.
In a previous article in the Journal of Visualized Experiments we have demonstrated skin microdialysis techniques for the collection of tissue-specific nociceptive and inflammatory biochemicals in humans. In this article we will show pain-testing paradigms that are often used in tandem with microdialysis procedures. Combining pain tests with microdialysis provides the critical link between behavioral and biochemical data that allows identifying key biochemicals responsible for generating and propagating pain. Two models of evoking pain in inflamed skin of human study participants are shown. The first model evokes pain with aid of heat stimuli. Heat evoked pain as described here is predominantly mediated by small, non-myelinated peripheral nociceptive nerve fibers (C-fibers). The second model evokes pain via punctuated pressure stimuli. Punctuated pressure evoked pain is predominantly mediated by small, myelinated peripheral nociceptive nerve fibers (A-delta fibers). The two models are mechanistically distinct and independently examine nociceptive processing by the two major peripheral nerve fiber populations involved in pain signaling. Heat pain is evoked with aid of the TSA II, a commercially available thermo-sensory analyzer (Medoc Advanced Medical Systems, Durham, NC). Stimulus configuration and delivery is handled with aid of specific software. Thermodes vary in size and shape but in principle consist of a metal plate that can be heated or cooled at various rates and for different periods of time. Algorithms assessing heat-evoked pain are manifold. In the experiments shown here, study participants are asked to indicate at what point they start experiencing pain while the thermode in contact with skin is heated at a predetermined rate starting at a temperature that does not evoke pain. The thermode temperature at which a subject starts experiencing pain constitutes the heat pain threshold. Mechanical pain is evoked with punctuated probes. Such probes are commercially available from several manufacturers (von Frey hairs). However, the accuracy of von Frey hairs has been criticized and many investigators use custom made punctuated pressure probes. In the experiments shown here eight custom-made punctuated probes of different weights are applied in consecutive order, a procedure called up-down algorithm, to identify perceptional deflection points, i.e., a change from feeling no pain to feeling pain or vice versa. The average weight causing a perceptional deflection constitutes the mechanical pain threshold.
Medicine, Issue 23, Experimental pain, experimental inflammation, human, skin, heat stimuli, mechanical stimuli, pain threshold, psychophysics, non-myelinated nociceptive nerve fiber, small myelinated nociceptive nerve fiber
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Vascular Occlusion Training for Inclusion Body Myositis: A Novel Therapeutic Approach
Authors: Bruno Gualano, Carlos Ugrinowitsch, Manoel Neves Jr., Fernanda R. Lima, Ana Lúcia S. Pinto, Gilberto Laurentino, Valmor A.A. Tricoli, Antonio H. Lancha Jr., Hamilton Roschel.
Institutions: University of São Paulo, University of São Paulo.
Inclusion body myositis (IBM) is a rare idiopathic inflammatory myopathy. It is known to produces remarkable muscle weakness and to greatly compromise function and quality of life. Moreover, clinical practice suggests that, unlike other inflammatory myopathies, the majority of IBM patients are not responsive to treatment with immunosuppressive or immunomodulatory drugs to counteract disease progression1. Additionally, conventional resistance training programs have been proven ineffective in restoring muscle function and muscle mass in these patients2,3. Nevertheless, we have recently observed that restricting muscle blood flow using tourniquet cuffs in association with moderate intensity resistance training in an IBM patient produced a significant gain in muscle mass and function, along with substantial benefits in quality of life4. Thus, a new non-pharmacological approach for IBM patients has been proposed. Herein, we describe the details of a proposed protocol for vascular occlusion associated with a resistance training program for this population.
Medicine, Issue 40, exercise training, therapeutical, myositis, vascular occlusion
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Assessment of Social Interaction Behaviors
Authors: Oksana Kaidanovich-Beilin, Tatiana Lipina, Igor Vukobradovic, John Roder, James R. Woodgett.
Institutions: Mount Sinai Hospital, Mount Sinai Hospital, University of Toronto, University of Toronto, University of Toronto.
Social interactions are a fundamental and adaptive component of the biology of numerous species. Social recognition is critical for the structure and stability of the networks and relationships that define societies. For animals, such as mice, recognition of conspecifics may be important for maintaining social hierarchy and for mate choice 1. A variety of neuropsychiatric disorders are characterized by disruptions in social behavior and social recognition, including depression, autism spectrum disorders, bipolar disorders, obsessive-compulsive disorders, and schizophrenia. Studies of humans as well as animal models (e.g., Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, Rattus norvegicus) have identified genes involved in the regulation of social behavior 2. To assess sociability in animal models, several behavioral tests have been developed (reviewed in 3). Integrative research using animal models and appropriate tests for social behavior may lead to the development of improved treatments for social psychopathologies. The three-chamber paradigm test known as Crawley's sociability and preference for social novelty protocol has been successfully employed to study social affiliation and social memory in several inbred and mutant mouse lines (e.g. 4-7). The main principle of this test is based on the free choice by a subject mouse to spend time in any of three box's compartments during two experimental sessions, including indirect contact with one or two mice with which it is unfamiliar. To quantitate social tendencies of the experimental mouse, the main tasks are to measure a) the time spent with a novel conspecific and b) preference for a novel vs. a familiar conspecific. Thus, the experimental design of this test allows evaluation of two critical but distinguishable aspects of social behavior, such as social affiliation/motivation, as well as social memory and novelty. "Sociability" in this case is defined as propensity to spend time with another mouse, as compared to time spent alone in an identical but empty chamber 7. "Preference for social novelty" is defined as propensity to spend time with a previously unencountered mouse rather than with a familiar mouse 7. This test provides robust results, which then must be carefully analyzed, interpreted and supported/confirmed by alternative sociability tests. In addition to specific applications, Crawley's sociability test can be included as an important component of general behavioral screen of mutant mice.
Neuroscience, Issue 48, Mice, behavioral test, phenotyping, social interaction
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
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Using Chronic Social Stress to Model Postpartum Depression in Lactating Rodents
Authors: Lindsay M. Carini, Christopher A. Murgatroyd, Benjamin C. Nephew.
Institutions: Tufts University Cummings School of Veterinary Medicine, Manchester Metropolitan University.
Exposure to chronic stress is a reliable predictor of depressive disorders, and social stress is a common ethologically relevant stressor in both animals and humans. However, many animal models of depression were developed in males and are not applicable or effective in studies of postpartum females. Recent studies have reported significant effects of chronic social stress during lactation, an ethologically relevant and effective stressor, on maternal behavior, growth, and behavioral neuroendocrinology. This manuscript will describe this chronic social stress paradigm using repeated exposure of a lactating dam to a novel male intruder, and the assessment of the behavioral, physiological, and neuroendocrine effects of this model. Chronic social stress (CSS) is a valuable model for studying the effects of stress on the behavior and physiology of the dam as well as her offspring and future generations. The exposure of pups to CSS can also be used as an early life stress that has long term effects on behavior, physiology, and neuroendocrinology.
Behavior, Issue 76, Neuroscience, Neurobiology, Physiology, Anatomy, Medicine, Biomedical Engineering, Neurobehavioral Manifestations, Mental Health, Mood Disorders, Depressive Disorder, Anxiety Disorders, behavioral sciences, Behavior and Behavior Mechanisms, Mental Disorders, Stress, Depression, Anxiety, Postpartum, Maternal Behavior, Nursing, Growth, Transgenerational, animal model
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
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Flying Insect Detection and Classification with Inexpensive Sensors
Authors: Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, Eamonn Keogh.
Institutions: University of California, Riverside, University of California, Riverside, University of São Paulo - USP, ISCA Technologies.
An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect’s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.
Bioengineering, Issue 92, flying insect detection, automatic insect classification, pseudo-acoustic optical sensors, Bayesian classification framework, flight sound, circadian rhythm
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
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Cross-Modal Multivariate Pattern Analysis
Authors: Kaspar Meyer, Jonas T. Kaplan.
Institutions: University of Southern California.
Multivariate pattern analysis (MVPA) is an increasingly popular method of analyzing functional magnetic resonance imaging (fMRI) data1-4. Typically, the method is used to identify a subject's perceptual experience from neural activity in certain regions of the brain. For instance, it has been employed to predict the orientation of visual gratings a subject perceives from activity in early visual cortices5 or, analogously, the content of speech from activity in early auditory cortices6. Here, we present an extension of the classical MVPA paradigm, according to which perceptual stimuli are not predicted within, but across sensory systems. Specifically, the method we describe addresses the question of whether stimuli that evoke memory associations in modalities other than the one through which they are presented induce content-specific activity patterns in the sensory cortices of those other modalities. For instance, seeing a muted video clip of a glass vase shattering on the ground automatically triggers in most observers an auditory image of the associated sound; is the experience of this image in the "mind's ear" correlated with a specific neural activity pattern in early auditory cortices? Furthermore, is this activity pattern distinct from the pattern that could be observed if the subject were, instead, watching a video clip of a howling dog? In two previous studies7,8, we were able to predict sound- and touch-implying video clips based on neural activity in early auditory and somatosensory cortices, respectively. Our results are in line with a neuroarchitectural framework proposed by Damasio9,10, according to which the experience of mental images that are based on memories - such as hearing the shattering sound of a vase in the "mind's ear" upon seeing the corresponding video clip - is supported by the re-construction of content-specific neural activity patterns in early sensory cortices.
Neuroscience, Issue 57, perception, sensory, cross-modal, top-down, mental imagery, fMRI, MRI, neuroimaging, multivariate pattern analysis, MVPA
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Using Learning Outcome Measures to assess Doctoral Nursing Education
Authors: Glenn H. Raup, Jeff King, Romana J. Hughes, Natasha Faidley.
Institutions: Harris College of Nursing and Health Sciences, Texas Christian University.
Education programs at all levels must be able to demonstrate successful program outcomes. Grades alone do not represent a comprehensive measurement methodology for assessing student learning outcomes at either the course or program level. The development and application of assessment rubrics provides an unequivocal measurement methodology to ensure a quality learning experience by providing a foundation for improvement based on qualitative and quantitatively measurable, aggregate course and program outcomes. Learning outcomes are the embodiment of the total learning experience and should incorporate assessment of both qualitative and quantitative program outcomes. The assessment of qualitative measures represents a challenge for educators in any level of a learning program. Nursing provides a unique challenge and opportunity as it is the application of science through the art of caring. Quantification of desired student learning outcomes may be enhanced through the development of assessment rubrics designed to measure quantitative and qualitative aspects of the nursing education and learning process. They provide a mechanism for uniform assessment by nursing faculty of concepts and constructs that are otherwise difficult to describe and measure. A protocol is presented and applied to a doctoral nursing education program with recommendations for application and transformation of the assessment rubric to other education programs. Through application of these specially designed rubrics, all aspects of an education program can be adequately assessed to provide information for program assessment that facilitates the closure of the gap between desired and actual student learning outcomes for any desired educational competency.
Medicine, Issue 40, learning, outcomes, measurement, program, assessment, rubric
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The use of Biofeedback in Clinical Virtual Reality: The INTREPID Project
Authors: Claudia Repetto, Alessandra Gorini, Cinzia Vigna, Davide Algeri, Federica Pallavicini, Giuseppe Riva.
Institutions: Istituto Auxologico Italiano, Università Cattolica del Sacro Cuore.
Generalized anxiety disorder (GAD) is a psychiatric disorder characterized by a constant and unspecific anxiety that interferes with daily-life activities. Its high prevalence in general population and the severe limitations it causes, point out the necessity to find new efficient strategies to treat it. Together with the cognitive-behavioral treatments, relaxation represents a useful approach for the treatment of GAD, but it has the limitation that it is hard to be learned. The INTREPID project is aimed to implement a new instrument to treat anxiety-related disorders and to test its clinical efficacy in reducing anxiety-related symptoms. The innovation of this approach is the combination of virtual reality and biofeedback, so that the first one is directly modified by the output of the second one. In this way, the patient is made aware of his or her reactions through the modification of some features of the VR environment in real time. Using mental exercises the patient learns to control these physiological parameters and using the feedback provided by the virtual environment is able to gauge his or her success. The supplemental use of portable devices, such as PDA or smart-phones, allows the patient to perform at home, individually and autonomously, the same exercises experienced in therapist's office. The goal is to anchor the learned protocol in a real life context, so enhancing the patients' ability to deal with their symptoms. The expected result is a better and faster learning of relaxation techniques, and thus an increased effectiveness of the treatment if compared with traditional clinical protocols.
Neuroscience, Issue 33, virtual reality, biofeedback, generalized anxiety disorder, Intrepid, cybertherapy, cyberpsychology
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.